Weighted Interaction Network






Select a file Example



Node degree:


Weights range: —— *



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Function:
Create a weighted network to visualize and analyze molecular interaction. Learn More~


Input:

The network input file should contain at least three columns which present the nodes (the first two columns) and the edge weights (the third column). Edge weight is the expression correlation coefficient of two genes. The node data could be gene names or IDs. The network input file must contain self-defined headers.


Parameters:

①Node degree: also called connectivity. There are two measurements to calculate node degree: hard threshold and soft threshold. The hard threshold means the edge numbers of each node. The soft threshold means the sum of edge weights of each node. For example, the node A interacts with node B with edge weight of 0.5 and node C with edge weight of 0.8. Then, the node degree of node A calculated by hard threshold is 2, and the node degree of node A calculated by soft threshold is 1.3 (0.5+0.8).

②Weights range: Only correlations with edge weights in this range will be constructed. Note: in the hard threshold mode, our tool will firstly pick up the weights in the setting weights range and then calculate the node degrees. Nevertheless, in the soft threshold mode, this tool will calculate the node degrees at first, then screen the weights based on the setting weights range.


Output:
A dynamic modifiable weighted network available to download after modifying in PNG/PDF/SVG formats. Legend of connectivity in SVG format is also downloadable.

Example:Boundary files  
Output:
生物云平台